Anhui Truchum Advanced Materials and Technology Co (002171) Fair Value & Analysis
Basic Materials · CN · Market cap 23.1B CNY
Analysis
Anhui Truchum Advanced Materials and Technology Co (002171) currently trades at ¥16.43, while our model-based Fair Value estimate is ¥4.19 — implying the stock looks roughly 74.5% overvalued today. We read business quality at 91/100 (high quality), in the Basic Materials sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Anhui Truchum Advanced Materials and Technology Co., Ltd. engages in the research, production, and sale of copper-based and steel-based materials, carbon fiber composite materials, special thermal equipment, and new materials in China and internationally. It offers copper alloy plate and strip products, such as brass, red copper and tin/phosphor bronze series products for use in military, coinage, energy conservation, automobiles, and high-speed rails industry; and high-end copper conductor products, including conductive copper rod, high-precision electrical round copper wire, tinned soft round copper wire, soft copper stranded wire, and other series. The company also provides brass wire rod for the cutting of high precision new material; high grade environmental-friendly brass wire rod for low zinc ornaments; high precision copper alloy Y-shaped zipper wire; extra-hard copper alloy spring wire for buttons; copper alloy inflating valve and valve core for tires, zipper flat wire, and…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.